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.DS_Store |
6.00KB |
.DS_Store |
6.00KB |
.DS_Store |
6.00KB |
.DS_Store |
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.DS_Store |
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.DS_Store |
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0_getting.py |
303B |
198810101_20151231.csv |
543.79KB |
1decision_tree_submit.py |
9.81KB |
1email_spam_tfidf_submit.py |
2.62KB |
1histogram.py |
529B |
1imputation.py |
3.25KB |
1one_hot_encode.py |
2.42KB |
1stock_price_prediction.py |
7.48KB |
20051201_20151210.csv |
644B |
2avazu_ctr.py |
2.06KB |
2clean_words.py |
723B |
2feature_selection.py |
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2linear_regression.py |
4.72KB |
2logistic_function.py |
833B |
2topic_categorization.py |
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3decision_tree_regression.py |
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3dimensionality_reduction.py |
635B |
3logistic_regression_from_scratch.py |
7.60KB |
3plot_rbf_kernels.py |
1.13KB |
3post_clustering.py |
919B |
4ctg.py |
1.14KB |
4generic_feature_engineering.py |
344B |
4random_forest_feature_selection.py |
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4support_vector_regression.py |
439B |
4topic_model.py |
998B |
5save_reuse_monitor_model.py |
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5scikit_logistic_regression.py |
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Best Practices in Data Preparation Stage.mp4 |
31.86MB |
Best Practices in the Deployment and Monitoring Stage.mp4 |
13.90MB |
Best Practices in the Model Training, Evaluation, and Selection Stage.mp4 |
10.84MB |
Best Practices in the Training Sets Generation Stage.mp4 |
20.46MB |
Brief Overview of Advertising Click-Through Prediction.mp4 |
11.00MB |
Brief Overview of the Stock Market And Stock Price.mp4 |
7.05MB |
Choosing Between the Linear and the RBF Kernel.mp4 |
14.21MB |
Classifier Performance Evaluation.mp4 |
36.98MB |
Click-Through Prediction with Decision Tree.mp4 |
24.99MB |
Click-Through Prediction with Logistic Regression by Gradient Descent.mp4 |
75.32MB |
Clustering.mp4 |
10.44MB |
config.py |
3.38KB |
CTG.xls |
1.66MB |
Data Acquisition and Feature Generation.mp4 |
12.29MB |
Data Preprocessing.mp4 |
9.15MB |
Decision Tree Classifier.mp4 |
36.69MB |
Decision Tree Regression.mp4 |
27.45MB |
email_spam.py |
10.28KB |
Exploring Naïve Bayes.mp4 |
5.10MB |
Feature Selection via Random Forest.mp4 |
16.04MB |
Fetal State Classification with SVM.mp4 |
21.84MB |
Getting Started with Classification.mp4 |
8.76MB |
Getting the Newsgroups Data.mp4 |
14.10MB |
globalnames |
1011B |
history |
14B |
Installing Software and Setting Up.mp4 |
22.01MB |
Introduction to Machine Learning.mp4 |
13.02MB |
Linear Regression.mp4 |
30.28MB |
Logistic Regression Classifier.mp4 |
37.40MB |
Machine Learning with Python.mp4 |
1.61MB |
Machine Learning with Python.mp4 |
1.61MB |
Model Tuning and cross-validation.mp4 |
18.26MB |
News topic Classification with Support Vector Machine.mp4 |
36.37MB |
objectdb |
2.21KB |
One-Hot Encoding - Converting Categorical Features to Numerical.mp4 |
21.42MB |
Predicting Stock Price with Regression Algorithms.mp4 |
24.42MB |
Random Forest - Feature Bagging of Decision Tree.mp4 |
18.28MB |
Recap and Inverse Document Frequency.mp4 |
16.63MB |
Regression Performance Evaluation.mp4 |
12.72MB |
Stock Price Prediction with Regression Algorithms.mp4 |
34.23MB |
Support Vector Regression.mp4 |
8.09MB |
The Course Overview.mp4 |
17.18MB |
The Implementations of Decision Tree.mp4 |
22.81MB |
The Implementations of SVM.mp4 |
19.68MB |
The Kernels of SVM.mp4 |
11.79MB |
The Mechanics of Naïve Bayes.mp4 |
7.33MB |
The Mechanics of SVM.mp4 |
9.16MB |
The Naïve Bayes Implementation.mp4 |
57.36MB |
Thinking about Features.mp4 |
20.34MB |
Topic Modeling.mp4 |
13.04MB |
Touring Powerful NLP Libraries in Python.mp4 |
40.29MB |
Understanding NLP.mp4 |
15.97MB |
Visualization.mp4 |
11.53MB |